Giter Club home page Giter Club logo

edtech-chat-bot's Introduction

Edtechmasters Chatbot

This project provides a Python chatbot built with Langchain, Chainlit, AWS Bedrock (Amazon Titan Embeddings G1 - Text and Anthropic's Claude LLM) to interact with users about educational resources.

Prerequisites

  • Python 3.12.1 (or a compatible version): This project requires a specific Python version to ensure compatibility with its dependencies. You can check your Python version by running python --version or python3 --version in your terminal. If you don't have the correct version, download it from https://www.python.org/downloads/.
  • virtualenv tool: It helps isolate project dependencies. Install it using pip install virtualenv if you haven't already.

Getting Started

This section provides instructions on how to set up the project's environment to run smoothly.

  1. Clone the Repository:

    Before setting up the environment, clone this repository from GitHub.

    This will clone the repository into a local directory named edtech-chat-bot. You can change this name if you prefer.

  2. Change Directory:

    Navigate into the project directory using the following command:

    cd edtech-chat-bot

Setting Up the Environment

  1. Create a Virtual Environment:

    1. Open your terminal and navigate to your project directory (where you cloned the repository).

    2. Create a virtual environment named venv (you can choose any name) using the following command:

      virtualenv venv
    3. Activate the virtual environment:

      • Windows:
        venv\Scripts\activate.bat
      • macOS/Linux:
        source venv/bin/activate

      The terminal prompt should change to indicate that the virtual environment is active (usually prefixed with the environment name).

  2. Install Dependencies

    (Optional) Environment Variables: The project might utilize environment variables stored in a .env file. If a file named .env-sample exists, copy it to .env and update the values according to the instructions within the .env-sample file. These variables might be essential for the project's functionality.

    Now that the virtual environment is activated, install the required packages listed in the requirements.txt file using the following command:

    pip install -r requirements.txt

    This will download and install all the necessary Python packages for your project within the isolated virtual environment.

  3. Verify Installation

    (Optional) After installation, you can try running a simple script from your project to ensure everything is set up correctly.

Running the Chatbot

  1. Start the Bot:

    Once you've completed the setup steps, you can start the chatbot using the following command:

    chainlit run chat.py --port 80

    Replace chat.py with the actual filename of your main chatbot script if it's named differently. This command instructs Chainlit to run the specified Python script (chat.py) and exposes it on port 80 (you can change the port number if needed).

    This will launch your chatbot in a web interface accessible from any web browser on your machine by visiting http://localhost:80 (or the port you specified).

Note:

  • Replace venv with the actual name you gave to your virtual environment.
  • Deactivate the virtual environment when you're done working on the project by running deactivate in your terminal.

By following these steps, you'll have a properly configured environment to run this Python chatbot project using Python 3.12.1 (or a compatible version) and its dependencies isolated within the virtual environment. You can then launch the chatbot using the provided command.

edtech-chat-bot's People

Contributors

i-do-dev avatar

Watchers

Kostas Georgiou avatar  avatar

Forkers

edtech-masters

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.